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While the pandemic has spurred digital transformation, even a corporate metaverse debate about the future of remote work, AI was not invaluable during the pandemic in fighting against Covid-19 directly. AI should have been able to warn us that a pandemic was coming, but it didn’t. Those few weeks of uncertainty were very costly in how countries prepared for what was to come.
Still AI in healthcare has made many little gains during the last two years, many of which have not been well publicized. As for a warning system of AI for the next pandemic, a recently announced early warning system designed by MedShr Insights may have the capability to predict pandemics. The capability fetched the technology third place honor in the Trinity Challenge and a prize of $660,000.
AI Shows Promise in Early Diagnosis and Detection
AI has improved in reading various medical scans and tests, to catch what humans miss. Early detection of diseases, dementia and many other conditions and hyper-personalizing the patient experience are certainly the abode of artificial intelligence’s impact on the future of healthcare. AI in pharma and drug discovery also has grown in leaps and bounds.
AI in healthcare is also somewhat controversial. Back in 2019, a group of healthcare specialists created an AI-based system that can predict the risk of premature death caused by chronic disease. For urgent situations where ICUs are full and doctors need to decide which Covid-19 patients to treat first or give priority to, AI should be making the call, as it’s very stressful for people to make those kinds of choices.
Future of AI in Healthcare and Need for Better AI Ethics Highlighted
AI will certainly be implicated in triage efficiency too, as well as preventative healthcare. Conditions like Long-covid (Long Haulers) will likely enable AI to learn which symptoms are most likely to lead to temporary disability. AI will also be used in the advent of biotechnology, human augmentation and medical ethics and the WHO created important guidelines around the use of AI in Healthcare. I find this fascinating as I think a lot about AI ethics.
What I especially like about the WHO guidelines and report about AI’s impact on healthcare is moderation vs. the hype. Their new ethics guidance cautions against overestimating the benefits of technology. This is important to realize as an abundance of headlines and research doesn’t mean AI is impacting the current reality of healthcare all that much.
The new guidance, Ethics & Governance of Artificial Intelligence for Health, is the result of two years of consultations held by a panel of international experts appointed by the WHO. While the WHO was possibly partly incompetent in certain aspects of the early stage pandemic, their awareness and attempt to make rules around AI’s use for a humanitarian sense is really one of the better models we have.
The World Health Organizations Principles Around AI
What follows is their quote directly from here.
Ultimately, guided by existing laws and human rights obligations, and new laws and policies that enshrine ethical principles, governments, providers, and designers must work together to address ethics and human rights concerns at every stage of an AI technologys design, development, and deployment.
Six principles to ensure AI works for the public interest in all countries
To limit the risks and maximize the opportunities intrinsic in the use of AI for health, the WHO provides the following principles as the basis for AI regulation and governance:
- Protecting human autonomy: In the context of health care, this means that humans should remain in control of health-care systems and medical decisions; privacy and confidentiality should be protected, and patients must give valid informed consent through appropriate legal frameworks for data protection.
2. Promoting human well-being and safety and the public interest. The designers of AI technologies should satisfy regulatory requirements for safety, accuracy and efficacy for well-defined use cases or indications. Measures of quality control in practice and quality improvement in the use of AI must be available.
3. Ensuring transparency, explainability and intelligibility. Transparency requires that sufficient information be published or documented before the design or deployment of an AI technology. Such information must be easily accessible and facilitate meaningful public consultation and debate on how the technology is designed and how it should or should not be used.
4. Fostering responsibility and accountability. Although AI technologies perform specific tasks, it is the responsibility of stakeholders to ensure that they are used under appropriate conditions and by appropriately trained people. Effective mechanisms should be available for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms.
5. Ensuring inclusiveness and equity. Inclusiveness requires that AI for health be designed to encourage the widest possible equitable use and access, irrespective of age, sex, gender, income, race, ethnicity, sexual orientation, ability or other characteristics protected under human rights codes.
6. Promoting AI that is responsive and sustainable. Designers, developers and users should continuously and transparently assess AI applications during actual use to determine whether AI responds adequately and appropriately to expectations and requirements. AI systems should also be designed to minimize their environmental consequences and increase energy efficiency. Governments and companies should address anticipated disruptions in the workplace, including training for health-care workers to adapt to the use of AI systems, and potential job losses due to use of automated systems.
Human Rights in the Metaverse AI-of-Everything World?
In the spirit of digital transformation a lot of progress is actually by-passing certain aspects of our human rights where legal regulation isn’t taking place. It would be a pity if AI’s impact on healthcare were one of these areas where data protection, privacy and the right to personal choice was not implemented in an orderly fashion. Since we know that companies such as Google, Amazon, Apple and others are getting aggressively into healthcare we must be vigilant to maintain a high ethical code of conduct around the impact of AI in healthcare.
While digital transformation has flourished during the pandemic, I don’t think we’ve seen a corresponding explosion of AI in healthcare breakthroughs as we have in other fields such as FinTech, the corporate metaverse (e.g. Microsoft Teams), home fitness or even telemedicine itself as a rapidly maturing industry. AI in healthcare is more ubiquitous but slow moving and becoming more active in academic research and medical R&D such as drug discovery in particular.
Benefits outweigh the Risks for AI in Healthcare
Europe appears to be thinking the most of how AI will impact healthcare among global bodies. Earlier this year, European health innovation network, EIT Health launched an AI report from its Think Tank, urging healthcare providers to invest more in AI and tech post-pandemic. Dozens of health tech startups are also utilizing AI in healthcare solutions and they will mature in the 2020s as will biotechnology companies that scale to the mainstream.
Dr Tedros Adhanom Ghebreyesus, WHO Director General, said: Like all new technology, AI holds enormous potential for improving the health of millions of people around the world, but like all technology it can also be misused and cause harm. Indeed the abuse of medical data and privacy abuses of technology coming closer to the home (as with remote work) brings up many questions as to AI’s impact on the data harvesting of people with special conditions. If the smart home is to become medically proficient with AI, how do the patients know where their data is going? If an E-commerce retailer knows which meds I get delivered or Apple builds an integrated EMR system, that’s a lot of our sensitive data potentially exposed to third parties.
AI will Soon Personalized Healthcare and Get More Personal as Our Intermediary with the World
Even more likely than us living in a metaverse is AI being embedded in our world, and dealing with our most intimate mental health, social, cognitive, and health related data. What are our human rights in such a world of AI permeating our health related environments? If my FitBit knows about my sleep patterns, will Google use that information to tailor Ads to me with predictive analytics? The reality of an AIoT world are both amazing and a little frightening. The impact of AI on our mental health life is particularly worrisome.
While technology leads to more loneliness in society as mobile time and streaming time cut into human time, will AI help us one day with a fake solution to our technological loneliness? These are some of the very real human questions around the use of AI in healthcare (much of it in the home) in the future. AI in healthcare has huge implications on major developments such as:
- Adventure of the brain-computer interface (BCI)
- AI’s impact on radiology, early detection scans and Big Data to personalize care
- Improving healthcare accessibility and inclusion to underserved populations and the most vulnerable
- Using predictive analytics on medical history related to family history for significant reduction in early detection of ailments
- Bringing Electronic Medical Records (EMR) into the cloud and tracking much more than typical EMR systems do, with more efficiency and embodied artificial intelligence.
- Dealing with large systemic issues like the rising cost of healthcare, the burden of antibiotic resistance, the problems associated with reduced global fertility rates, the rising percentage of the elderly (not to mention the next pandemic).
Conclusion: AI in Healthcare is Just Beginning
The pandemic has not been aided by AI by and large, but we have a better frame of reference for what the AI of healthcare will entail in the 2020s and 2030s with many new developments related to healthcare.
The AI of Healthcare will have distinct costs and benefits, and medical professionals will increasingly work in an AI-human hybrid system. Medical devices, machines and robotics (including robotic surgery) will take decades to improve and be refined.
Globally in the 2020s, AI in healthcare is just in its infancy. For data scientists and knowledge workers it’s clear machine learning will become more implicated in the years ahead in making clinical decisions with better data. Medical transcriptions and software that helps doctors reduce their task load is already accelerating at a rapid pace.
Several types of AI are already being employed by payers and providers of care, and life sciences companies. AI is just exploring what’s possible to improve and revolutionize healthcare, improve longevity and make healthcare more affordable and accessible to all. While AI contributes to aspects of dystopia in some ways, AI in Healthcare is one of the key ways that AI can help us move to a world that more resembles a utopia. AI’s impact in healthcare is so radically good the entire narrative of ‘AI for Good’ may hinge upon it.
As for knowledge workers in the datascience and machine learning realm, we will need talent to make AI in Healthcare a reality. The quality of life for millions of people may depend upon it.